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220822 ||| eng |
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|a books978-3-0365-2044-5
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|a 9783036520445
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|a 9783036520438
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| 100 |
1 |
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|a Congalton, Russell G.
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| 245 |
0 |
0 |
|a Mapping and Monitoring Forest Cover
|h Elektronische Ressource
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| 260 |
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|a Basel, Switzerland
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2021
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| 300 |
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|a 1 electronic resource (144 p.)
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| 653 |
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|a satellite remote sensing
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| 653 |
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|a Sentinel-2
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| 653 |
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|a forest monitoring
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| 653 |
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|a land cover classification
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| 653 |
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|a degradation
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| 653 |
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|a canopy height model
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| 653 |
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|a allometric equation
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| 653 |
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|a regeneration
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| 653 |
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|a above-ground biomass
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| 653 |
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|a n/a
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| 653 |
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|a Forest Inventory and Analysis
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| 653 |
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|a vegetation
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| 653 |
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|a Juniperus
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| 653 |
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|a land-use
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| 653 |
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|a forest cover map
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| 653 |
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|a individual tree crown
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| 653 |
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|a forest sampling
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| 653 |
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|a Ruoergai area
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| 653 |
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|a aerial images
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| 653 |
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|a geospatial-temporal analysis
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| 653 |
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|a forest change
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| 653 |
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|a national forest inventory
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| 653 |
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|a inventory efficiency
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| 653 |
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|a segmentation
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| 653 |
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|a Savitzky-Golay filtering
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| 653 |
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|a trend
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| 653 |
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|a remote sensing
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| 653 |
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|a unmanned aerial systems
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| 653 |
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|a spatial and temporal analysis
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| 653 |
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|a Research and information: general / bicssc
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| 653 |
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|a NDVI
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| 653 |
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|a multisensory approach
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| 700 |
1 |
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|a Congalton, Russell G.
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 028 |
5 |
0 |
|a 10.3390/books978-3-0365-2044-5
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| 856 |
4 |
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|u https://www.mdpi.com/books/pdfview/book/4343
|7 0
|x Verlag
|3 Volltext
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| 856 |
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|u https://directory.doabooks.org/handle/20.500.12854/76873
|z DOAB: description of the publication
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| 082 |
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|a 000
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| 520 |
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|a This book is a compilation of six papers that provide some valuable information about mapping and monitoring forest cover using remotely sensed imagery. Examples include mapping large areas of forest, evaluating forest change over time, combining remotely sensed imagery with ground inventory information, and mapping forest characteristics from very high spatial resolution data. Together, these results demonstrate effective techniques for effectively learning more about our very important forest resources.
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